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Record W4285370496 · doi:10.1386/ijmec_00032_1

Participation in an early childhood music programme and socioemotional development: A meta-analysis

2021· article· en· W4285370496 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Music in Early Childhood · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsUniversité LavalUniversité du Québec à MontréalUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsSocioemotional selectivity theoryModerationPsychologyEarly childhoodMeta-analysisDevelopmental psychologyObservational studySocial psychologyMedicine

Abstract

fetched live from OpenAlex

Music is increasingly recognized as having a social role, insofar as it is linked to emotional regulation and to early interactions in infancy and the preschool years. The goal of this meta-analysis was to examine the impact of participating in an early childhood music programme on indices of socioemotional development in children under 6 years of age. The overall result showed a moderate effect size ( N = 681, k = 11, d = 0.57, p < 0.001). Moderation analyses revealed that the type of assessment (observational measure, reported measure or other types of assessment) significantly influenced effect size ( Q′ = 25.26, p < 0.001). No other moderation analysis was significant. Although these findings are promising, suggesting that participation in an early childhood music programme contribute to children’s socioemotional development, more rigorous studies are needed to assess the impact of participating in a music programme on socioemotional development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.941
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.096
GPT teacher head0.286
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it